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University of Cross River State
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MMS-TTS outperformed other models in generating stable long-form speech for Efik, but tonal inaccuracies reveal critical gaps in TTS for low-resource languages.
NLLB-200 can be effectively fine-tuned for low-resource languages like Efik, even with a relatively small, community-curated dataset, achieving surprisingly strong translation performance.
